Explore the potential of Large Language Models (LLMs) in enhancing recommendation systems through tool learning in this 15-minute conference talk presented at SIGIR 2024. Delve into the innovative approach proposed by authors Yuyue Zhao, Jiancan Wu, Xiang Wang, Wei Tang, Dingxian Wang, and Maarten de Rijke as they discuss how LLMs can be empowered to perform recommendation tasks autonomously. Gain insights into the integration of prompts, instructions, and LLMs in recommender systems, and discover how this novel technique aims to revolutionize personalized content delivery and user experience.
Let Me Do It For You: Towards LLM Empowered Recommendation via Tool Learning
Association for Computing Machinery (ACM) via YouTube
Overview
Syllabus
SIGIR 2024 T2.5 [fp] Let Me Do It For You: Towards LLM Empowered Recommendation via Tool Learning
Taught by
Association for Computing Machinery (ACM)
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